Learning via collaboration has gained much success over past few decades given
their learning benefits. Group composition has been seen as a relevant design element that
contributes to the potential effectiveness of collaborative learning. To support practitioners in
this context this paper addresses the problem of automatic group formation implementing
policies related to well-known collaboration techniques and considering personal attributes in
across-spaces contexts where multiple activities, ...
Learning via collaboration has gained much success over past few decades given
their learning benefits. Group composition has been seen as a relevant design element that
contributes to the potential effectiveness of collaborative learning. To support practitioners in
this context this paper addresses the problem of automatic group formation implementing
policies related to well-known collaboration techniques and considering personal attributes in
across-spaces contexts where multiple activities, places and tools are involved in a learning
situation. Analytics of contextual and progress-in-activity information about learners
presented as a summary would support practitioners to obtain a comprehensive knowledge
about them to subsequently facilitate formation of effective collaborative groups to face
forthcoming activities. The paper discusses a work in progress web based architecture of a
group formation service to compute groupings which also assists in recommending grouping
constraints via learning analytics which will facilitate practitioners in the adaptive set-up of
the group formation design element across-spaces.
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